It's All in Your Head

Cognitive Neuroscience Explained

Cognitive neuroscience (C/NS) is a field of science that explores the brain systems responsible for behavior and cognition. Studies in C/NS result in a better understanding of brain function and help to identify techniques to augment mental stability. C/NS has had a vast influence on modern-day living, especially in healthcare, education, and technology applications.

In the workplace, cognitive neuroscience carries significant prospects related to facilitating productivity and decision-making. Better decision-making and heightened productivity have been recorded among those who underwent mindfulness training - an activity that reduces stress and increases focus (Davidson et al., 2003; Tang et al., 2007). Brain activity tracking wearable technology can also identify the most productive periods and create schedules to optimize production (Rahman et al., 2020).

AI and Cognitive Neuroscience

AI and cognitive neuroscience maintain an undeniable bond with each other. Within this interconnectedness, cognitive neuroscience provides invaluable observations into the processing of information by the brain. The insights gained by researchers can provide guidance as to what must be incorporated into AI algorithms. One example of the link between the two fields is illustrated by the usage of neuroimaging methodologies by researchers to analyze the manner in which the brain processes visual information. Studies into cognitive neuroscience have led to computer vision algorithms that could identify faces and objects with greater accuracy (Zhang et al., 2015).

In cognitive neuroscience research, AI is an invaluable tool with multifaceted uses. One such way is through the implementation of machine learning algorithms to decipher patterns in vast datasets, which in turn allows for better predictions of brain activity (Liu et al., 2018). Researchers can also use AI to construct cognitive process simulations that help develop and test theories about the inner workings of the brain (Gershman et al., 2015). AI's growth has caused researchers to focus their studies on how the brain performs functions in the presence of AI systems and how people interact with intelligent machines (Friston et al., 2018).

Conclusion

Overall, the impact of cognitive neuroscience on society and business has been significant, leading to new insights into the brain and new applications in healthcare, education, and technology. As research in this field continues to advance, we can expect to see further innovations and applications that improve our understanding of the brain and improve our lives.

References

Davidson, R. J., Kabat-Zinn, J., Schumacher, J., Rosenkranz, M., Muller, D., Santorelli, S. F., … & Sheridan, J. F. (2003). Alterations in brain and immune function produced by mindfulness meditation. Psychosomatic Medicine, 65(4), 564-570.

Friston, K., Parr, T., & de Vries, B. (2018). The graphical brain: Belief propagation and active inference. Network Neuroscience, 2(3), 284-305.

Gershman, S. J., Horvitz, E. J., & Tenenbaum, J. B. (2015). Computational rationality: A converging paradigm for intelligence in brains, minds, and machines. Science, 349(6245), 273-278.

Liu, T., & Duann, J. R. (2018). Applying deep learning models to predicting neuroimaging data. In Predictive Modeling of Drug Sensitivity (pp. 191-212). Humana Press.

Rahman, M. A., Shafique, M., & Song, B. (2020). Smart wearable devices in industry 4.0: A review of literature and challenges. Journal of Manufacturing Systems, 54, 43-62.

Tang, Y. Y., Ma, Y., Wang, J., Fan, Y., Feng, S., Lu, Q., … & Posner, M. I. (2007). Short-term meditation training improves attention and self-regulation. Proceedings of the National Academy of Sciences, 104(43), 17152-17156.

Zhang, L., Lin, L., Liang, X., He, K., & Sun, J. (2015). Is faster R-CNN doing well for pedestrian detection?. In 2015 IEEE international conference on computer vision (ICCV) (pp. 1089–1097). IEEE.It'